This study used a computerized simulation and problem-solving tool along with artificial neural networks (ANN) as pattern recognizers to identify the common types of strategies high school and college undergraduate chemistry students would use to solve qualitative chemistry problems. Participants were 134 high school chemistry students who used the Interactive Multi-Media Exercises (IMMEX) software with a problem set related to identification of hazardous materials. Then, based on the calculated probabilities that students would transition between these strategy types over time, hidden chain Markov analysis allowed two objectives to be accomplished. A model of the capacity of the current curriculum to produce students able to apply chemistry content to real world problems was developed, and then this model was used to suggest pedagogical interventions that might be most effective at promoting better student understanding and as a metric by which to evaluate the potential effectiveness of these and other interventions. (Contains 9 tables and 15 references.) (SLD)